[Numpy-discussion] Speed degression?

[Travis Oliphant]

Steffen Loeck wrote:
> Hi all,
>
> i made some speed tests using the sin-function and the %-operation to compare 
> Numeric, numpy 0.9.8 and numpy 0.9.9.2732. 
> As result the latest numpy version seems to be very slow in comparison to the 
> two other candidates.
>
> Results (in usec per loop):
>                                      sin-array            mod-array  
>                                     
>  Numeric                                134                   18         
>   
>  numpy 0.9.8                             97                   55
>
>  numpy 0.9.9.2732                       204                  316
>    
>  numpy 0.9.8 + math                      38
>
>  numpy 0.9.9.2732 + math                161
>   
>  Numeric + math                          23
>
>
> The used scripts can be found at the end. 
>
> Can anyone verify my results and explain the observed speed degression?
>   

I can't verify the results, but it's possible that the indexing code for 
a single integer is a bit slower.  

However, you forgot to test the "use Python lists" approach which is the 
fastest of all on this code. 

python -m timeit -s "x = [0.1]*10;" "for i in xrange(9): 
x[i+1]=(x[i]+1.1)%(1.0)"


Using Numeric/NumPy is always slower than lists if you are doing 
element-by-element processing.   NumPy is slower than Numeric for such 
processing.  But, Numeric was always slower than pure Python too for 
such processing.  So, the moral of the story is:

"don't compute like that with NumPy (or Numeric)"

With that said.   I can add back the 1-d integer check in the indexing 
code to see if that speeds things up...

-Travis